queue_prune_plan

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It explicitly discloses the key behavioral trait: this tool is read-only and only produces a plan, it does not modify the queue because Spotify lacks a queue-removal endpoint. It also mentions optional handling of podcast episodes. However, it doesn't disclose what happens with the plan output (e.g., whether it includes track URIs, counts, or a re-queue list format), nor does it address rate limits or whether the queue is fetched live or from a snapshot.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences and front-loads the core purpose. Every sentence earns its place: the first states the plan and optional episodes, the second explains the Spotify limitation and the plan nature, the third confirms read-only. No wasted words, but the read-only tag is a bit redundant with the first sentence's 'plan' emphasis.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only planner with two optional parameters, the description is mostly complete. However, there is no output schema and the description doesn't explain what the 'clean re-queue list' looks like (e.g., plain URIs, track names, counts) or how the agent should act on the plan. Also, it doesn't mention whether the plan is applied automatically or left to the user, though it does say 'you act on with queue playback.' That's sufficient but could use more detail about the emitted plan's structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters (drop_episodes and response_format) with defaults and descriptions. The tool description adds minimal extra meaning: it mentions 'podcast episodes' which maps to drop_episodes. It doesn't add details about response_format values beyond what the schema provides, but that's acceptable given full schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifies a precise verb ('Plan'), the resource ('upcoming queue'), and the action ('identify redundant duplicate entries... and emit a clean re-queue list'). It also clearly distinguishes itself from a direct mutation by stating 'Spotify has no queue-removal endpoint, so this is a plan you act on with queue playback.' This clearly separates it from sibling tools like remove_from_queue or queue_replace_via_playlist.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly communicates when to use this tool: when the user wants to prune the upcoming queue and needs a plan rather than direct action. It implies when not to use it: when a direct mutation is needed, since Spotify has no queue-removal endpoint. It doesn't explicitly name alternative tools for direct queue manipulation, but it does state the constraint that forces this to be a plan, which is strong contextual guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.